Adaptive quantization for instance-based mesh coding

ABSTRACT

A method and apparatus comprising computer code configured to cause a processor or processors to obtain an input mesh comprising volumetric data of at least one three-dimensional (3D) visual content, derive a plurality of submeshes of the input mesh from a frame of the volumetric data, set bitdepths to a first submesh and a second submesh from the submeshes, a first bitdepth being different than a second bitdepth, quantize the first submesh and the second submesh based on respective ones of the first bitdepth and the second bitdepth, and signal a result of quantizing the first submesh and the second submesh.

CROSS REFERENCE TO RELATED APPLICATION

The present application claims priority to provisional application U.S.63/359,749 filed on Jul. 8, 2022 which is hereby expressly incorporatedby reference, in its entirety, into the present application.

BACKGROUND 1. Field

The present disclosure is directed a set of advanced video codingtechnologies including both lossless and lossy mesh coding technologiesbased on instances and bitdepths of meshes.

2. Description of Related Art

The advances in 3D capture, modeling, and rendering have promoted theubiquitous presence of 3D contents across several platforms and devices.Nowadays, it is possible to capture a baby's first step in one continentand allow the grandparents to see (and maybe interact) and enjoy a fullimmersive experience with the child in another continent. Nevertheless,in order to achieve such realism, models are becoming ever moresophisticated, and a significant amount of data is linked to thecreation and consumption of those models.

VMesh is an ongoing MPEG standard to compress the static and dynamicmesh. VMesh separates the input mesh into a simplified base mesh and aresidual mesh. The base mesh may be encoded at high quality while theremainder mesh may be encoded with subdivision surface fitting anddisplacement encoding to exploit local characteristic.

However, a complex mesh often contains information about multipleinstances to relate associate texture maps. This information isavailable at the encoding time. On the other hand, a mesh could besegmented into several parts based on their characteristics. Forexample, there are more polygons in the face region of a human mesh.

As such, a constant quantization step size applied for all instances,objects, parts in mesh leads to a large quantization error, mesh regionsmay not be not equally important, the number of faces may be variedsignificantly in different parts of a mesh, and a base mesh could besimpler than original mesh and the displacement, thus could require lessaccuracy in bitdepth. And for any of those reasons there is therefore adesire for technical solutions to such problems that arose in videocoding technology.

SUMMARY

There is included a method and apparatus comprising memory configured tostore computer program code and a processor or processors configured toaccess the computer program code and operate as instructed by thecomputer program code. The computer program is configured to cause theprocessor implement obtaining code configured to cause the at least oneprocessor to obtaining code configured to cause the at least oneprocessor to obtain volumetric data of at least one three-dimensional(3D) visual content, deriving code configured to cause the at least oneprocessor to derive a plurality of submeshes from a frame of thevolumetric data, each of the submeshes comprising a respective one ofinstances of objects, and at least two of the submeshes overlap eachother in the frame, setting code configured to cause the at least oneprocessor to set a first bitdepth to a first one of the at least two ofthe submeshes and a second bitdepth to a second one of the at least twoof the submeshes, the first bitdepth being different than the secondbitdepth, quantizing code configured to cause the at least one processorto quantize the at least two of the submeshes based on respective onesof the first bitdepth and the second bitdepth, and signaling codeconfigured to cause the at least one processor to signal a result ofquantizing the at least two of the submeshes.

According to various embodiments, the volumetric data comprises the atleast two of the submeshes overlapped with each other and bounded by abounding box, deriving the plurality of submeshes comprises boundingeach of the instances of the object by respective ones of secondbounding boxes, and, at any of the first bitdepth and the secondbitdepth, a quantization step size of any of the at least two of thesubmeshes is less than a quantization step size of the at least two ofthe submeshes overlapped with each other and bounded by the boundingbox.

According to various embodiments, setting the first bitdepth is based ondetermining a first face density of the first one of the at least two ofthe submeshes, and wherein setting the second bitdepth is based ondetermining a second face density of the second one of the at least twoof the submeshes.

According to various embodiments, quantizing the at least two of thesubmeshes comprises: applying, based on the first bitdepth, a firstlevel of quantization to the first one of the at least two of thesubmeshes, and applying, based on the second bitdepth, a second level ofquantization to the second one of the at least two of the submeshes, andwherein the first level is set to be less than the second level based ondetermining that the first bitdepth indicates that the first one of theat least two of the submeshes has a greater one of the face densitiesthan indicated by the second bitdepth set to the second one of the atleast two submeshes.

According to various embodiments, the first one of the at least twosubmeshes is bounded by a first one of the second bounding boxes, thesecond one of the at least two submeshes is bounded by a second one ofthe second bounding boxes, and determining the first face density andthe second face density comprises comparing numbers of faces of thefirst one of the at least two submeshes and the second one of the atleast two submeshes to respective ones of volumes of the first one ofthe second bounding boxes and the second one of the second boundingboxes.

According to various embodiments, signaling the result of quantizing theat least two of the submeshes comprises signaling that each of the atleast two of the submeshes shares a same bounding box offset.

According to various embodiments, signaling the result of quantizing theat least two of the submeshes comprises signaling a total number of theinstances of the objects in the frame.

According to various embodiments, signaling the result of quantizing theat least two of the submeshes comprises signaling a difference betweenquantization applied to the at least two of the submeshes and sortingthe difference as compared to other quantization applied to othersubmeshes of the frame.

According to various embodiments, the first bitdepth is applied to atleast one other of the other submeshes, and signaling the result ofquantizing the at least two of the submeshes comprises grouping thefirst one of the at least two of the submeshes with the at least oneother of the other submeshes based on determining that the firstbitdepth is applied to both the first one of the at least two of thesubmeshes and the at least one other of the other submeshes.

According to various embodiments, setting the first bitdepth and thesecond bitdepth comprises deriving mean square errors of each of the atleast two submeshes at each of the first bitdepth and the secondbitdepth.

BRIEF DESCRIPTION OF THE DRAWINGS

Further features, nature, and various advantages of the disclosedsubject matter will be more apparent from the following detaileddescription and the accompanying drawings in which:

FIG. 1 is a schematic illustrations of a diagram in accordance withembodiments.

FIG. 2 is a simplified block diagram in accordance with embodiments.

FIG. 3 is a simplified illustration in accordance with embodiments.

FIG. 4 is a simplified illustration in accordance with embodiments.

FIG. 5 is a simplified illustration in accordance with embodiments.

FIG. 6 is a simplified illustration in accordance with embodiments.

FIG. 7 is a simplified illustration in accordance with embodiments.

FIG. 8 is a simplified illustration in accordance with embodiments.

FIG. 9 is a simplified illustration in accordance with embodiments.

FIG. 10 is a simplified illustration in accordance with embodiments.

FIG. 11 is a simplified illustration in accordance with embodiments.

FIG. 12 is a simplified illustration in accordance with embodiments.

FIG. 13 is a simplified flow diagram in accordance with embodiments.

FIG. 14 is a simplified flow diagram in accordance with embodiments.

FIG. 15 is a simplified flow diagram in accordance with embodiments.

FIG. 16 is a simplified illustration in accordance with embodiments.

FIG. 17 is a simplified illustration in accordance with embodiments.

FIG. 18 is a simplified illustration in accordance with embodiments.

FIG. 19 is a simplified illustration in accordance with embodiments.

FIG. 20 is a simplified flow diagram in accordance with embodiments.

FIG. 21 is a simplified illustration in accordance with embodiments.

FIG. 22 is a simplified flow diagram in accordance with embodiments.

FIG. 23 is a simplified diagram in accordance with embodiments.

DETAILED DESCRIPTION

The proposed features discussed below may be used separately or combinedin any order. Further, the embodiments may be implemented by processingcircuitry (e.g., one or more processors or one or more integratedcircuits). In one example, the one or more processors execute a programthat is stored in a non-transitory computer-readable medium.

FIG. 1 illustrates a simplified block diagram of a communication system100 according to an embodiment of the present disclosure. Thecommunication system 100 may include at least two terminals 102 and 103interconnected via a network 105. For unidirectional transmission ofdata, a first terminal 103 may code video data at a local location fortransmission to the other terminal 102 via the network 105. The secondterminal 102 may receive the coded video data of the other terminal fromthe network 105, decode the coded data and display the recovered videodata. Unidirectional data transmission may be common in media servingapplications and the like.

FIG. 1 illustrates a second pair of terminals 101 and 104 provided tosupport bidirectional transmission of coded video that may occur, forexample, during videoconferencing. For bidirectional transmission ofdata, each terminal 101 and 104 may code video data captured at a locallocation for transmission to the other terminal via the network 105.Each terminal 101 and 104 also may receive the coded video datatransmitted by the other terminal, may decode the coded data and maydisplay the recovered video data at a local display device.

In FIG. 1 , the terminals 101, 102, 103 and 104 may be illustrated asservers, personal computers and smart phones but the principles of thepresent disclosure are not so limited. Embodiments of the presentdisclosure find application with laptop computers, tablet computers,media players and/or dedicated video conferencing equipment. The network105 represents any number of networks that convey coded video data amongthe terminals 101, 102, 103 and 104, including for example wirelineand/or wireless communication networks. The communication network 105may exchange data in circuit-switched and/or packet-switched channels.Representative networks include telecommunications networks, local areanetworks, wide area networks and/or the Internet. For the purposes ofthe present discussion, the architecture and topology of the network 105may be immaterial to the operation of the present disclosure unlessexplained herein below.

FIG. 2 illustrates, as an example for an application for the disclosedsubject matter, the placement of a video encoder and decoder in astreaming environment. The disclosed subject matter can be equallyapplicable to other video enabled applications, including, for example,video conferencing, digital TV, storing of compressed video on digitalmedia including CD, DVD, memory stick and the like, and so on.

A streaming system may include a capture subsystem 203, that can includea video source 201, for example a digital camera, creating, for example,an uncompressed video sample stream 213. That sample stream 213 may beemphasized as a high data volume when compared to encoded videobitstreams and can be processed by an encoder 202 coupled to the videosource 201, which may be for example a camera as discussed above. Theencoder 202 can include hardware, software, or a combination thereof toenable or implement aspects of the disclosed subject matter as describedin more detail below. The encoded video bitstream 204, which may beemphasized as a lower data volume when compared to the sample stream,can be stored on a streaming server 205 for future use. One or morestreaming clients 212 and 207 can access the streaming server 205 toretrieve copies 208 and 206 of the encoded video bitstream 204. A client212 can include a video decoder 211 which decodes the incoming copy ofthe encoded video bitstream 208 and creates an outgoing video samplestream 210 that can be rendered on a display 209 or other renderingdevice (not depicted). In some streaming systems, the video bitstreams204, 206 and 208 can be encoded according to certain videocoding/compression standards. Examples of those standards are notedabove and described further herein.

FIG. 3 may be a functional block diagram of a video decoder 300according to an embodiment of the present invention.

A receiver 302 may receive one or more codec video sequences to bedecoded by the decoder 300; in the same or another embodiment, one codedvideo sequence at a time, where the decoding of each coded videosequence is independent from other coded video sequences. The codedvideo sequence may be received from a channel 301, which may be ahardware/software link to a storage device which stores the encodedvideo data. The receiver 302 may receive the encoded video data withother data, for example, coded audio data and/or ancillary data streams,that may be forwarded to their respective using entities (not depicted).The receiver 302 may separate the coded video sequence from the otherdata. To combat network jitter, a buffer memory 303 may be coupled inbetween receiver 302 and entropy decoder/parser 304 (“parser”henceforth). When receiver 302 is receiving data from a store/forwarddevice of sufficient bandwidth and controllability, or from anisosychronous network, the buffer 303 may not be needed, or can besmall. For use on best effort packet networks such as the Internet, thebuffer 303 may be required, can be comparatively large and canadvantageously of adaptive size.

The video decoder 300 may include a parser 304 to reconstruct symbols313 from the entropy coded video sequence. Categories of those symbolsinclude information used to manage operation of the decoder 300, andpotentially information to control a rendering device such as a display312 that is not an integral part of the decoder but can be coupled toit. The control information for the rendering device(s) may be in theform of Supplementary Enhancement Information (SEI messages) or VideoUsability Information (VUI) parameter set fragments (not depicted). Theparser 304 may parse/entropy-decode the coded video sequence received.The coding of the coded video sequence can be in accordance with a videocoding technology or standard, and can follow principles well known to aperson skilled in the art, including variable length coding, Huffmancoding, arithmetic coding with or without context sensitivity, and soforth. The parser 304 may extract from the coded video sequence, a setof subgroup parameters for at least one of the subgroups of pixels inthe video decoder, based upon at least one parameters corresponding tothe group. Subgroups can include Groups of Pictures (GOPs), pictures,tiles, slices, macroblocks, Coding Units (CUs), blocks, Transform Units(TUs), Prediction Units (PUs) and so forth. The entropy decoder/parsermay also extract from the coded video sequence information such astransform coefficients, quantizer parameter values, motion vectors, andso forth.

The parser 304 may perform entropy decoding/parsing operation on thevideo sequence received from the buffer 303, so to create symbols 313.The parser 304 may receive encoded data, and selectively decodeparticular symbols 313. Further, the parser 304 may determine whetherthe particular symbols 313 are to be provided to a Motion CompensationPrediction unit 306, a scaler/inverse transform unit 305, an IntraPrediction Unit 307, or a loop filter 311.

Reconstruction of the symbols 313 can involve multiple different unitsdepending on the type of the coded video picture or parts thereof (suchas: inter and intra picture, inter and intra block), and other factors.Which units are involved, and how, can be controlled by the subgroupcontrol information that was parsed from the coded video sequence by theparser 304. The flow of such subgroup control information between theparser 304 and the multiple units below is not depicted for clarity.

Beyond the functional blocks already mentioned, decoder 300 can beconceptually subdivided into a number of functional units as describedbelow. In a practical implementation operating under commercialconstraints, many of these units interact closely with each other andcan, at least partly, be integrated into each other. However, for thepurpose of describing the disclosed subject matter, the conceptualsubdivision into the functional units below is appropriate.

A first unit is the scaler/inverse transform unit 305. Thescaler/inverse transform unit 305 receives quantized transformcoefficient as well as control information, including which transform touse, block size, quantization factor, quantization scaling matrices,etc. as symbol(s) 313 from the parser 304. It can output blockscomprising sample values, that can be input into aggregator 310.

In some cases, the output samples of the scaler/inverse transform 305can pertain to an intra coded block; that is: a block that is not usingpredictive information from previously reconstructed pictures, but canuse predictive information from previously reconstructed parts of thecurrent picture. Such predictive information can be provided by an intrapicture prediction unit 307. In some cases, the intra picture predictionunit 307 generates a block of the same size and shape of the block underreconstruction, using surrounding already reconstructed informationfetched from the current (partly reconstructed) picture 309. Theaggregator 310, in some cases, adds, on a per sample basis, theprediction information the intra prediction unit 307 has generated tothe output sample information as provided by the scaler/inversetransform unit 305.

In other cases, the output samples of the scaler/inverse transform unit305 can pertain to an inter coded, and potentially motion compensatedblock. In such a case, a Motion Compensation Prediction unit 306 canaccess reference picture memory 308 to fetch samples used forprediction. After motion compensating the fetched samples in accordancewith the symbols 313 pertaining to the block, these samples can be addedby the aggregator 310 to the output of the scaler/inverse transform unit(in this case called the residual samples or residual signal) so togenerate output sample information. The addresses within the referencepicture memory form where the motion compensation unit fetchesprediction samples can be controlled by motion vectors, available to themotion compensation unit in the form of symbols 313 that can have, forexample X, Y, and reference picture components. Motion compensation alsocan include interpolation of sample values as fetched from the referencepicture memory when sub-sample exact motion vectors are in use, motionvector prediction mechanisms, and so forth.

The output samples of the aggregator 310 can be subject to various loopfiltering techniques in the loop filter unit 311. Video compressiontechnologies can include in-loop filter technologies that are controlledby parameters included in the coded video bitstream and made availableto the loop filter unit 311 as symbols 313 from the parser 304, but canalso be responsive to meta-information obtained during the decoding ofprevious (in decoding order) parts of the coded picture or coded videosequence, as well as responsive to previously reconstructed andloop-filtered sample values.

The output of the loop filter unit 311 can be a sample stream that canbe output to the render device 312 as well as stored in the referencepicture memory 557 for use in future inter-picture prediction.

Certain coded pictures, once fully reconstructed, can be used asreference pictures for future prediction. Once a coded picture is fullyreconstructed and the coded picture has been identified as a referencepicture (by, for example, parser 304), the current reference picture 309can become part of the reference picture buffer 308, and a fresh currentpicture memory can be reallocated before commencing the reconstructionof the following coded picture.

The video decoder 300 may perform decoding operations according to apredetermined video compression technology that may be documented in astandard, such as ITU-T Rec. H.265. The coded video sequence may conformto a syntax specified by the video compression technology or standardbeing used, in the sense that it adheres to the syntax of the videocompression technology or standard, as specified in the videocompression technology document or standard and specifically in theprofiles document therein. Also necessary for compliance can be that thecomplexity of the coded video sequence is within bounds as defined bythe level of the video compression technology or standard. In somecases, levels restrict the maximum picture size, maximum frame rate,maximum reconstruction sample rate (measured in, for example megasamplesper second), maximum reference picture size, and so on. Limits set bylevels can, in some cases, be further restricted through HypotheticalReference Decoder (HRD) specifications and metadata for HRD buffermanagement signaled in the coded video sequence.

In an embodiment, the receiver 302 may receive additional (redundant)data with the encoded video. The additional data may be included as partof the coded video sequence(s). The additional data may be used by thevideo decoder 300 to properly decode the data and/or to more accuratelyreconstruct the original video data. Additional data can be in the formof, for example, temporal, spatial, or signal-to-noise ratio (SNR)enhancement layers, redundant slices, redundant pictures, forward errorcorrection codes, and so on.

FIG. 4 may be a functional block diagram of a video encoder 400according to an embodiment of the present disclosure.

The encoder 400 may receive video samples from a video source 401 (thatis not part of the encoder) that may capture video image(s) to be codedby the encoder 400.

The video source 401 may provide the source video sequence to be codedby the encoder (303) in the form of a digital video sample stream thatcan be of any suitable bit depth (for example: 8 bit, 10 bit, 12 bit, .. . ), any colorspace (for example, BT.601 Y CrCB, RGB, . . . ) and anysuitable sampling structure (for example Y CrCb 4:2:0, Y CrCb 4:4:4). Ina media serving system, the video source 401 may be a storage devicestoring previously prepared video. In a videoconferencing system, thevideo source 401 may be a camera that captures local image informationas a video sequence. Video data may be provided as a plurality ofindividual pictures that impart motion when viewed in sequence. Thepictures themselves may be organized as a spatial array of pixels,wherein each pixel can comprise one or more samples depending on thesampling structure, color space, etc. in use. A person skilled in theart can readily understand the relationship between pixels and samples.The description below focuses on samples.

According to an embodiment, the encoder 400 may code and compress thepictures of the source video sequence into a coded video sequence 410 inreal time or under any other time constraints as required by theapplication. Enforcing appropriate coding speed is one function ofController 402. Controller controls other functional units as describedbelow and is functionally coupled to these units. The coupling is notdepicted for clarity. Parameters set by controller can include ratecontrol related parameters (picture skip, quantizer, lambda value ofrate-distortion optimization techniques, . . . ), picture size, group ofpictures (GOP) layout, maximum motion vector search range, and so forth.A person skilled in the art can readily identify other functions ofcontroller 402 as they may pertain to video encoder 400 optimized for acertain system design.

Some video encoders operate in what a person skilled in the art readilyrecognizes as a “coding loop.” As an oversimplified description, acoding loop can consist of the encoding part of an encoder 400 (“sourcecoder” henceforth) (responsible for creating symbols based on an inputpicture to be coded, and a reference picture(s)), and a (local) decoder406 embedded in the encoder 400 that reconstructs the symbols to createthe sample data that a (remote) decoder also would create (as anycompression between symbols and coded video bitstream is lossless in thevideo compression technologies considered in the disclosed subjectmatter). That reconstructed sample stream is input to the referencepicture memory 405. As the decoding of a symbol stream leads tobit-exact results independent of decoder location (local or remote), thereference picture buffer content is also bit exact between local encoderand remote encoder. In other words, the prediction part of an encoder“sees” as reference picture samples exactly the same sample values as adecoder would “see” when using prediction during decoding. Thisfundamental principle of reference picture synchronicity (and resultingdrift, if synchronicity cannot be maintained, for example because ofchannel errors) is well known to a person skilled in the art.

The operation of the “local” decoder 406 can be the same as of a“remote” decoder 300, which has already been described in detail abovein conjunction with FIG. 3 . Briefly referring also to FIG. 4 , however,as symbols are available and en/decoding of symbols to a coded videosequence by entropy coder 408 and parser 304 can be lossless, theentropy decoding parts of decoder 300, including channel 301, receiver302, buffer 303, and parser 304 may not be fully implemented in localdecoder 406.

An observation that can be made at this point is that any decodertechnology except the parsing/entropy decoding that is present in adecoder also necessarily needs to be present, in substantially identicalfunctional form, in a corresponding encoder. The description of encodertechnologies can be abbreviated as they are the inverse of thecomprehensively described decoder technologies. Only in certain areas amore detail description is required and provided below.

As part of its operation, the source coder 403 may perform motioncompensated predictive coding, which codes an input frame predictivelywith reference to one or more previously-coded frames from the videosequence that were designated as “reference frames.” In this manner, thecoding engine 407 codes differences between pixel blocks of an inputframe and pixel blocks of reference frame(s) that may be selected asprediction reference(s) to the input frame.

The local video decoder 406 may decode coded video data of frames thatmay be designated as reference frames, based on symbols created by thesource coder 403. Operations of the coding engine 407 may advantageouslybe lossy processes. When the coded video data may be decoded at a videodecoder (not shown in FIG. 4 ), the reconstructed video sequencetypically may be a replica of the source video sequence with someerrors. The local video decoder 406 replicates decoding processes thatmay be performed by the video decoder on reference frames and may causereconstructed reference frames to be stored in the reference picturememory 405, which may be for example a cache. In this manner, theencoder 400 may store copies of reconstructed reference frames locallythat have common content as the reconstructed reference frames that willbe obtained by a far-end video decoder (absent transmission errors).

The predictor 404 may perform prediction searches for the coding engine407. That is, for a new frame to be coded, the predictor 404 may searchthe reference picture memory 405 for sample data (as candidate referencepixel blocks) or certain metadata such as reference picture motionvectors, block shapes, and so on, that may serve as an appropriateprediction reference for the new pictures. The predictor 404 may operateon a sample block-by-pixel block basis to find appropriate predictionreferences. In some cases, as determined by search results obtained bythe predictor 404, an input picture may have prediction references drawnfrom multiple reference pictures stored in the reference picture memory405.

The controller 402 may manage coding operations of the source coder 403,which may be for example a video coder, including, for example, settingof parameters and subgroup parameters used for encoding the video data.

Output of all aforementioned functional units may be subjected toentropy coding in the entropy coder 408. The entropy coder translatesthe symbols as generated by the various functional units into a codedvideo sequence, by loss-less compressing the symbols according totechnologies known to a person skilled in the art as, for exampleHuffman coding, variable length coding, arithmetic coding, and so forth.

The transmitter 409 may buffer the coded video sequence(s) as created bythe entropy coder 408 to prepare it for transmission via a communicationchannel 411, which may be a hardware/software link to a storage devicewhich would store the encoded video data. The transmitter 409 may mergecoded video data from the source coder 403 with other data to betransmitted, for example, coded audio data and/or ancillary data streams(sources not shown).

The controller 402 may manage operation of the encoder 400. Duringcoding, the controller 402 may assign to each coded picture a certaincoded picture type, which may affect the coding techniques that may beapplied to the respective picture. For example, pictures often may beassigned as one of the following frame types:

An Intra Picture (I picture) may be one that may be coded and decodedwithout using any other frame in the sequence as a source of prediction.Some video codecs allow for different types of Intra pictures,including, for example Independent Decoder Refresh Pictures. A personskilled in the art is aware of those variants of I pictures and theirrespective applications and features.

A Predictive picture (P picture) may be one that may be coded anddecoded using intra prediction or inter prediction using at most onemotion vector and reference index to predict the sample values of eachblock.

A Bi-directionally Predictive Picture (B Picture) may be one that may becoded and decoded using intra prediction or inter prediction using atmost two motion vectors and reference indices to predict the samplevalues of each block. Similarly, multiple-predictive pictures can usemore than two reference pictures and associated metadata for thereconstruction of a single block.

Source pictures commonly may be subdivided spatially into a plurality ofsample blocks (for example, blocks of 4×4, 8×8, 4×8, or 16×16 sampleseach) and coded on a block-by-block basis. Blocks may be codedpredictively with reference to other (already coded) blocks asdetermined by the coding assignment applied to the blocks' respectivepictures. For example, blocks of I pictures may be codednon-predictively or they may be coded predictively with reference toalready coded blocks of the same picture (spatial prediction or intraprediction). Pixel blocks of P pictures may be coded non-predictively,via spatial prediction or via temporal prediction with reference to onepreviously coded reference pictures. Blocks of B pictures may be codednon-predictively, via spatial prediction or via temporal prediction withreference to one or two previously coded reference pictures.

The encoder 400, which may be for example a video coder, may performcoding operations according to a predetermined video coding technologyor standard, such as ITU-T Rec. H.265. In its operation, the encoder 400may perform various compression operations, including predictive codingoperations that exploit temporal and spatial redundancies in the inputvideo sequence. The coded video data, therefore, may conform to a syntaxspecified by the video coding technology or standard being used.

In an embodiment, the transmitter 409 may transmit additional data withthe encoded video. The source coder 403 may include such data as part ofthe coded video sequence. Additional data may comprisetemporal/spatial/SNR enhancement layers, other forms of redundant datasuch as redundant pictures and slices, Supplementary EnhancementInformation (SEI) messages, Visual Usability Information (VUI) parameterset fragments, and so on.

FIG. 5 illustrates a simplified block-style workflow diagram 500 ofexemplary view-port dependent processing an in Omnidirectional MediaApplication Format (OMAF) that may allow for 360-degree virtual reality(VR360) streaming described in OMAF.

At acquisition block 1001, video data A is acquired, such as data ofmultiple images and audio of same time instances in a case that theimage data may represent scenes in VR360. At processing block 1003, theimages B_(i) of the same time instance are processed by one or more ofbeing stitched, mapped onto a projected picture with respect to one ormore virtual reality (VR) angles or other angles/viewpoint(s) andregion-wise packed. Additionally, metadata may be created indicating anyof such processed information and other information so as to assist indelivering and rendering processes.

With respect to data D, at image encoding block 1005, the projectedpictures are encoded to data E_(i) and composed into a media file, andin viewport-independent streaming, and at video encoding block 1004, thevideo pictures are encoded as data E_(v) as a single-layer bitstream,for example, and with respect to data B_(a) the audio data may also beencoded into data E_(a) at audio encoding block 1002.

The data E_(a), E_(v), and E_(i), the entire coded bitstream F_(i)and/or F may be stored at a (content delivery network (CDN)/cloud)server, and typically may be fully transmitted, such as at deliveryblock 1007 or otherwise, to an OMAF player 1020 and may be fully decodedby a decoder such that at least an area of a decoded picturecorresponding to a current viewport is rendered to the user at displayblock 1016 with respect to the various metadata, file playback, andorientation/viewport metadata, such as an angle at which a user may belooking through a VR image device with respect to viewportspecifications of that device, from the head/eye tracking block 1008. Adistinct feature of VR360 is that only a viewport may be displayed atany particular time, and such feature may be utilized to improve theperformance of omnidirectional video systems, through selective deliverydepending on the user's viewport (or any other criteria, such asrecommended viewport timed metadata). For example, viewport-dependentdelivery may be enabled by tile-based video coding according toexemplary embodiments.

As with the encoding blocks described above, the OMAF player 1020according to exemplary embodiments may similarly reverse one or morefacets of such encoding with respect to the file/segment decapsulationof one or more of the data F′ and/or F′_(i) and metadata, decode theaudio data E′_(i) at audio decoding block 1010, the video data E′_(v) atvideo decoding block 1013, and the image data E′_(i) at image decodingblock 1014 to proceed with audio rendering of the data B′_(a) at audiorendering block 1011 and image rendering of the data D′ at imagerendering block 1015 so as to output, in a VR360 format according tovarious metadata such as the orientation/viewport metadata, display dataA′_(i) at display block 1016 and audio data A′_(s) at theloudspeakers/headphones block 1012. The various metadata may influenceones of the data decoding and rendering processes depending on varioustracks, languages, qualities, views, that may be selected by or for auser of the OMAF player 1020, and it is to be understood that the orderof processing described herein is presented for exemplary embodimentsand may be implemented in other orders according to other exemplaryembodiments.

FIG. 6 illustrates a simplified block-style content flow process diagram600 for (coded) point cloud data with view-position and angle dependentprocessing of point cloud data (herein “V-PCC”) with respect tocapturing/generating/(de)coding/rendering/displaying 6 degree-of-freedommedia. It is to be understood that the described features may be usedseparately or combined in any order and elements such as for encodingand decoding, among others illustrated, may be implemented by processingcircuitry (e.g., one or more processors or one or more integratedcircuits), and the one or more processors may execute a program that isstored in a non-transitory computer-readable medium according toexemplary embodiments.

The diagram 600 illustrates exemplary embodiments for streaming of codedpoint cloud data according to V-PCC.

At the volumetric data acquisition block 1101, a real-world visual sceneor a computer-generated visual scene (or combination of them) may becaptured by a set of camera devices or synthesized by a computer as avolumetric data, and the volumetric data, which may have an arbitraryformat, may be converted to a (quantized) point cloud data format,through image processing at the converting to point cloud block 1102.For example, data from the volumetric data may be area data by area dataconverted into ones of points of the point cloud by pulling one or moreof the values described below from the volumetric data and anyassociated data into a desired point cloud format according to exemplaryembodiments. According to exemplary embodiments, the volumetric data maybe a 3D data set of 2D images, such as slices from which a 2D projectionof the 3D data set may be projected for example. According to exemplaryembodiments, point cloud data formats include representations of datapoints in one or more various spaces and may be used to represent thevolumetric data and may offer improvements with respect to sampling anddata compression, such as with respect to temporal redundancies, and,for example, a point cloud data in an x, y, z, format representing, ateach point of multiple points of the cloud data, color values (e.g.,RGB, etc.), luminance, intensity, etc. and could be used withprogressive decoding, polygon meshing, direct rendering, octree 3Drepresentations of 2D quadtree data.

At projection to images block 1103, the acquired point cloud data may beprojected onto 2D images and encoded as image/video pictures withvideo-based point cloud coding (V-PCC). The projected point cloud datamay be composed of attributes, geometry, occupancy map, and othermetadata used for point cloud data reconstruction such as with painter'salgorithms, ray casting algorithms, (3D) binary space partitionalgorithms, among others for example.

At the scene generator block 1109, on the other hand, a scene generatormay generate some metadata to be used for rendering and displaying 6degrees-of-freedom (DoF) media, by a director's intention or a user'spreference for example. Such 6 DoF media may include the 360VR like 3Dviewing of a scene from rotational changes on 3D axis X, Y, Z inaddition to additional dimension allowing for movement front/back,up/down, and left/right with respect to a virtual experience within orat least according to point cloud coded data. The scene descriptionmetadata defines one or more scene composed of the coded point clouddata and other media data, including VR360, light field, audio, etc. andmay be provided to one or more cloud servers and or file/segmentencapsulation/decapsulation processing as indicated in FIG. 6 andrelated descriptions.

After video encoding block 1104 and image encoding block 1105 similar tothe video and image encoding described above (and as will be understood,audio encoding also may be provided as described above), file/segmentencapsulation block 1106 processes such that the coded point cloud dataare composed into a media file for file playback or a sequence of aninitialization segment and media segments for streaming according to aparticular media container file format such as one or more videocontainer formats and such as may be used with respect to DASH describedbelow, among others as such descriptions represent exemplaryembodiments. The file container also may include the scene descriptionmetadata, such as from the scene generator block 1109, into the file orthe segments.

According to exemplary embodiments, the file is encapsulated dependingon the scene description metadata to include at least one view positionand at least one or more angle views at that/those view position(s) eachat one or more times among the 6DoF media such that such file may betransmitted on request depending on user or creator input. Further,according to exemplary embodiments, a segment of such file may includeone or more portions of such file such as a portion of that 6DoF mediaindicating a single viewpoint and angle thereat at one or more times;however, these are merely exemplary embodiments and may be changeddepending on various conditions such as network, user, creatorcapabilities and inputs.

According to exemplary embodiments, the point cloud data is partitionedinto multiple 2D/3D regions, which are independently coded such as atone or more of video encoding block 1104 and image encoding block 1105.Then, each independently coded partition of point cloud data mayencapsulated at file/segment encapsulation block 1106 as a track in afile and/or segement. According to exemplary embodiments, each pointcloud track and/or a metadata track may include some useful metadata forview-position/angle dependent processing.

According to exemplary embodiments, the metadata, such as included in afile and/or segment encapsulated with respect to the file/segmentencapsulation block, useful for the view-position/angle dependentprocessing includes one or more of the following: layout information of2D/3D partitions with indices, (dynamic) mapping information associatinga 3D volume partition with one or more 2D partitions (e.g. any of atile/tile group/slice/sub-picture), 3D positions of each 3D partition ona 6DoF coordinate system, representative view position/angle lists,selected view position/angle lists corresponding to a 3D volumepartition, indices of 2D/3D partitions corresponding to a selected viewposition/angle, quality (rank)information of each 2D/3D partition, andrendering information of each 2D/3D partition for example depending oneach view position/angle. Calling on such metadata when requested, suchas by a user of the V-PCC player or as directed by a content creator forthe user of the V-PCC player, may allow for more efficient processingwith respect to specific portions of the 6DoF media desired with respectto such metadata such that the V-PCC player may deliver higher qualityimages of focused on portions of the 6DoF media than other portionsrather than delivering unused portions of that media.

From the file/segment encapsulation block 1106, the file or one or moresegments of the file may be delivered using a delivery mechanism (e.g.,by Dynamic Adaptive Streaming over HTTP (DASH)) directly to any of theV-PCC player 1125 and a cloud server, such as at the cloud server block1107 at which the cloud server can extract one or more tracks and/or oneor more specific 2D/3D partitions from a file and may merge multiplecoded point cloud data into one data.

According to data such as with the position/viewing angle tracking block1108, if the current viewing position and angle(s) is/are defined on a6DoF coordinate system, at a client system, then the view-position/anglemetadata may be delivered, from the file/segment encapsulation block1106 or otherwise processed from the file or segments already at thecloud server, at cloud server block 1107 such that the cloud sever mayextract appropriate partition(s) from the store file(s) and merge them(if necessary) depending on the metadata from the client system havingthe V-PCC player 1125 for example, and the extracted data can bedelivered to the client, as a file or segments.

With respect to such data, at the file/segment decapsulation block 1115,a file decapsulator processes the file or the received segments andextracts the coded bitstreams and parses the metadata, and at videodecoding and image decoding blocks, the coded point cloud data are thendecoded into decoded and reconstructed, at point cloud reconstructionblock 1112, to point cloud data, and the reconstructed point cloud datacan be displayed at display block 1114 and/or may first be composeddepending on one or more various scene descriptions at scene compositionblock 1113 with respect to scene description data according to the scenegenerator block 1109.

In view of the above, such exemplary V-PCC flow represents advantageswith respect to a V-PCC standard including one or more of the describedpartitioning capabilities for multiple 2D/3D areas, a capability of acompressed domain assembly of coded 2D/3D partitions into a singleconformant coded video bitstream, and a bitstream extraction capabilityof coded 2D/3D of a coded picture into conformant coded bitstreams,where such V-PCC system support is further improved by includingcontainer formation for a VVC bitstream to support a mechanism tocontain metadata carrying one or more of the above-described metadata.

In that light and according to exemplary embodiments further describedbelow, the term “mesh” indicates a composition of one or more polygonsthat describe the surface of a volumetric object. Each polygon isdefined by its vertices in 3D space and the information of how thevertices are connected, referred to as connectivity information.Optionally, vertex attributes, such as colors, normals, etc., could beassociated with the mesh vertices. Attributes could also be associatedwith the surface of the mesh by exploiting mapping information thatparameterizes the mesh with 2D attribute maps. Such mapping may bedescribed by a set of parametric coordinates, referred to as UVcoordinates or texture coordinates, associated with the mesh vertices.2D attribute maps are used to store high resolution attributeinformation such as texture, normals, displacements etc. Suchinformation could be used for various purposes such as texture mappingand shading according to exemplary embodiments.

Nonetheless, a dynamic mesh sequence may require a large amount of datasince it may consist of a significant amount of information changingover time. Therefore, efficient compression technologies are required tostore and transmit such contents. Mesh compression standards IC,MESHGRID, FAMC were previously developed by MPEG to address dynamicmeshes with constant connectivity and time varying geometry and vertexattributes. However, these standards do not take into account timevarying attribute maps and connectivity information. DCC (DigitalContent Creation) tools usually generate such dynamic meshes. Incounterpart, it is challenging for volumetric acquisition techniques togenerate a constant connectivity dynamic mesh, especially under realtime constraints. This type of contents is not supported by the existingstandards. According to exemplary embodiments herein, there is describedaspects of a new mesh compression standards to directly handle dynamicmeshes with time varying connectivity information and optionally timevarying attribute maps, this standard targets lossy, and losslesscompression for various applications, such as real-time communications,storage, free viewpoint video, AR and VR. Functionalities such as randomaccess and scalable/progressive coding are also considered.

FIG. 7 represents an example framework 700 of one dynamic meshcompression such as for a 2D atlas sampling based method. Each frame ofthe input meshes 1201 can be preprocessed by a series of operations,e.g., tracking, remeshing, parameterization, voxelization. Note that,these operations can be encoder-only, meaning they might not be part ofthe decoding process and such possibility may be signaled in metadata bya flag such as indicating 0 for encoder only and 1 for other. Afterthat, one can get the meshes with 2D UV atlases 1202, where each vertexof the mesh has one or more associated UV coordinates on the 2D atlas.Then, the meshes can be converted to multiple maps, including thegeometry maps and attribute maps, by sampling on the 2D atlas. Thenthese 2D maps can be coded by video/image codecs, such as HEVC, VVC,AV1, AVS3, etc. On the decoder 1203 side, the meshes can bereconstructed from the decoded 2D maps. Any post-processing andfiltering can also be applied on the reconstructed meshes 1204. Notethat other metadata might be signaled to the decoder side for thepurpose of 3D mesh reconstruction. Note that the chart boundaryinformation, including the uv and xyz coordinates, of the boundaryvertices can be predicted, quantized and entropy coded in the bitstream.The quantization step size can be configured in the encoder side totradeoff between the quality and the bitrates.

In some implementations, a 3D mesh can be partitioned into severalsegments (or patches/charts). Each segment is composed of a set ofconnected vertices associated with their geometry, attribute, andconnectivity information. As illustrated in the example 800 ofvolumetric data in FIG. 8 , the UV parameterization process 1302 ofmapping from 3D mesh segments onto 2D charts, such as to the above noted2D UV atlases 1202 block, maps one or more mesh segments 1301 onto a 2Dchart 1303 in the 2D UV atlas 1304. Each vertex (v_(n)) in the meshsegment will be assigned with a 2D UV coordinates in the 2D UV atlas.Note that the vertices (v_(n)) in a 2D chart form a connected componentas their 3D counterpart. The geometry, attribute, and connectivityinformation of each vertex can be inherited from their 3D counterpart aswell. For example, information may be indicated that vertex v₄ connectsdirectly to vertices v₀, v₅, v₁, and v₃, and similarly information ofeach of the other vertices may also be likewise indicated. Further, such2D texture mesh would, according to exemplary embodiments, furtherindicate information, such as color information, in a patch-by-patchbasis such as by patches of each triangle, e.g., v₂, v₅, v₃.

For example, further to the features of the example 800 of FIG. 8 , seethe example 900 of FIG. 9 where the 3D mesh segment 1301 can be alsomapped to multiple separate 2D charts 1401 and 1402. In this case, avertex in 3D could corresponds to multiple vertices in 2D UV atlas. Asshown in FIG. 9 , the same 3D mesh segment is mapped to multiple 2Dcharts, instead of a single chart as in FIG. 8 , in the 2D UV atlas. Forexample, 3D vertices v₁ and v₄ each have two 2D correspondencesv₁,v_(1′), and v₄, v_(4 ′), respectively. As such, a general 2D UV atlasof a 3D mesh may consist of multiple charts as shown in FIG. 14 , whereeach chart may contain multiple (usually more than or equal to 3)vertices associated with their 3D geometry, attribute, and connectivityinformation.

FIG. 10 shows an example 1000 illustrating a derived triangulation in achart with boundary vertices B₀, B₁, B₂, B₃, B₄, B₅, B₆, B₇. Whenpresented with such information, any triangulation method can be appliedto create connectivity among the vertices (including boundary verticesand sampled vertices). For example, for each vertex, find the closesttwo vertices. Or for all vertices, continuously generate triangles untila minimum number of triangles is achieved after a set number of tries.As shown in the example 1000, there are various regularly shaped,repeating triangles and various oddly shaped triangles, generallyclosest to the boundary vertices, having their own unique dimensionsthat may or may not be shared with any other of the triangles. Theconnectivity information can be also reconstructed by explicitsignaling. If a polygon cannot be recovered by implicit rules, theencoder can signal the connectivity information in the bitstreamaccording to exemplary embodiments.

Viewing the above-described patches, the example 1000 may represent onesuch patch, such a patch formed of vertices v₃, v₂, vs shown in any ofFIGS. 14 and 15 .

Boundary vertices B₀, B₁, B₂, B₃, B₄, B₅, B₆, B₇ are defined in the 2DUV space. As shown in FIG. 15 , the filled vertices are boundaryvertices because they are on the boundary edges of a connected component(a patch/chart). A boundary edge can be determined by checking if theedge is only appeared in one triangle. The following information ofboundary vertices is significant and should be signaled in the bitstreamaccording to exemplary embodiments: geometry information, e.g., the 3DXYZ coordinates even though currently in the 2D UV parametric form, andthe 2D UV coordinates.

For a case in which a boundary vertex in 3D corresponds to multiplevertices in 2D UV atlas, such as shown in FIG. 9 , the mapping from 3DXUZ to 2D UV can be one-to-multiple. Therefore, a UV-to-XYZ (or referredto as UV2XYZ) index can be signaled to indicate the mapping function.UV2XYZ may be a 1D-array of indices that correspond each 2D UV vertex toa 3D XYZ vertex.

According to exemplary embodiments, to represent a mesh signalefficiently, a subset of the mesh vertices may be coded first, togetherwith the connectivity information among them. In the original mesh, theconnection among these vertices may not exist as they are subsampledfrom the original mesh. There are different ways to signal theconnectivity information among the vertices, and such subset istherefore referred to as the base mesh or as base vertices.

Other vertices, however, can be predicted by applying interpolationbetween two or more already decoded mesh vertices. A predictor vertexwill have its geometry location along the edge of two connected existingvertices, so the geometry information of the predictor can be calculatedbased on the neighboring decoded vertices. In some cases, thedisplacement vector or prediction error, from the to-be-coded vertex tothe vertex predictor, is to be further coded. For example, see theexample 1100 of FIG. 11 , an example of such edge-based vertexprediction is shown or more specifically of vertex geometry predictionusing intra prediction by extrapolation by extending a triangle to aparallelogram, as shown on the left, and interpolation by weightedaveraging of two existing vertices as shown in the right. After decodingthe base vertices (i.e. the solid triangle 1801 in FIG. 11 left),interpolation among these base vertices can be done along the connectededges. For example, the middle point of each edge can be generated aspredictors. The geometry locations of these interpolated points aretherefore (weighted) average of the two neighboring decoded vertices(the dashed points 1802 in FIG. 11 left). Having more than 1 middlepoint between two already decoded vertices can also be done in a similarway. The actual vertices to be coded can therefore be reconstructed byadding the displacement vectors to the predictors (FIG. 7 middle). Afterdecoding these additional vertices, the connection among the newlydecoded vertices and the existing base vertices are still maintained. Inaddition, connection among the newly decoded vertices can be furtherestablished. Together with the base vertices, more intermediate verticespredictors can be generated along the new edges (FIG. 7 right) byconnecting these newly decoded vertices 1803 and base vertices together.Therefore, more actual vertices to be decoded are present withassociated displacement vectors.

According to exemplary embodiments, mesh vertices of a mesh frame 1902can also be predicted from decoded vertices of a previously coded meshframe 1901. This prediction mechanism is referred to as interprediction. Examples of mesh geometry inter prediction are illustratedin the example 1200 of FIG. 12 showing vertex geometry prediction usinginter prediction (previous mesh frame's vertices become predictors ofcurrent frame's vertices). In some cases, the displacement vector orprediction error, from the to-be-coded vertex to the vertex predictor,is to be further coded.

According to exemplary embodiments, a number of methods are implementedfor dynamic mesh compression and are part of the above-mentionededge-based vertex prediction framework, where a base mesh is coded firstand then more additional vertices are predicted based on theconnectivity information from the edges of the base mesh. Note that theycan be applied individually or by any form of combinations.

For example, consider the vertex grouping for prediction mode exampleflowchart 1300 of FIG. 13 . At S201, vertices inside a mesh may beobtained and can be divided at S202 into different groups for predictionpurposes, for example see FIG. 10 . In one example, the division is doneusing the patch/chart partitioning at S204 as previously discussed. Inanother example, the division is done under each patch/chart S205. Thedecision S203 whether to proceed to S204 or S205 may be signaled by aflag or the like. In the case of S205, several vertices of the samepatch/chart form a prediction group and will share the same predictionmode, while several other vertices of the same patch/chart can useanother prediction mode. Such grouping at S206 can be assigned atdifferent levels by determining respective number of vertices involvedper group. For example, every 64, 32 or 16 vertices following a scanorder inside a patch/chart will be assigned the same prediction modeaccording to exemplary embodiments and other vertices may be differentlyassigned. For each group, a prediction mode can be intra prediction modeor inter prediction mode. This can be signaled or assigned. According tothe example flowchart 1300, if a mesh frame or mesh slice is determinedto be in intra type at S207, such as by checking whether a flag of thatmesh frame or mesh slice indicates an intra type, then all groups ofvertices inside that mesh frame or mesh slice shall use intra predictionmode; otherwise, at S208 either intra prediction or inter predictionmode may be chosen per group for all vertices therein.

Further, for a group of mesh vertices using intra prediction mode, itsvertices can only be predicted by using previously coded vertices insidethe same sub-partition of the current mesh. Sometimes the sub-partitioncan be the current mesh itself according to exemplary embodiments, andfor a group of mesh vertices using inter prediction mode, its verticescan only be predicted by using previously coded vertices from anothermesh frame according to exemplary embodiments. Each of the above-notedinformation may be determined and signaled by a flag or the like. Saidprediction features may occur at S210 and results of said prediction andsignaling may occur at S211

According to exemplary embodiments, for each vertex in a group ofvertices in the example flowchart 1300 and in the flowchart 1400described below, after prediction, the residue will be a 3D displacementvector, indicating the shift from the current vertex to its predictor.The residues of a group of vertices need to be further compressed. Inone example, transformation at S211, along with the signaling thereof,can be applied to the residues of a vertex group, before entropy coding.The following methods may be implemented to handle the coding of a groupof displacement vectors. For example, in one method, to properly signalthe case where a group of displacement vectors, some displacementvectors, or its components have only zero values. In another embodiment,a flag is signaled for each displacement vectors whether this vector hasany non-zero component, and if no, the coding of all components for thisdisplacement vector can be skipped. Further, in another embodiment, aflag is signaled for each group of displacement vectors whether thisgroup has any non-zero vectors, and if no, the coding of alldisplacement vectors of this group can be skipped. Further, in anotherembodiment, a flag is signaled for each component of a group ofdisplacement vectors whether this component of the group has anynon-zero vectors, and if no, the coding of this component of alldisplacement vectors s of this group can be skipped. Further, in anotherembodiment, there may be a signaling of the case where a group ofdisplacement vectors, or a component of the group of displacementvectors, needs a transformation, and if not, the transformation can beskipped, and quantization/entropy coding can be directly applied to thegroup or the group components. Further, in another embodiment, a flagmay be signaled for each group of displacement vectors whether thisgroup needs to go through transformation, and if no, the transformcoding of all displacement vectors of this group can be skipped.Further, in another embodiment, a flag is signaled for each component ofa group of displacement vectors whether this component of the groupneeds to go through transformation, and if no, the transform coding ofthis component of all displacement vectors of this group can be skipped.The above-described embodiments in this paragraph, which regard handlingof vertex prediction residues, may also be combined and implemented inparallel on different patches respectively.

FIG. 14 shows the example flowchart 1400 where, at S221 a mesh frame canbe obtained coded as an entire data unit, meaning all vertices orattributes of the mesh frame may have correlation among them.Alternatively, depending on a determination at S222, a mesh frame can bedivided at S223 into smaller independent sub-partitions, similar inconcept to slices or tiles in 2D videos or images. A coded mesh frame ora coded mesh sub-partition can be assigned with a prediction type atS224. Possible prediction types include intra coded type and inter codedtype. For intra coded type, only predictions from the reconstructedparts of the same frame or slice are allowed at S225. On the other hand,an inter prediction type will allow at S225 predictions from apreviously coded mesh frame, in addition to intra mesh framepredictions. Further, inter prediction type may be classified with moresub-types such as P type or B type. In P type, only one predictor can beused for prediction purposes, while in B type, two predictors, from twopreviously coded mesh frames, may be used to generate the predictor.Weighted average of the two predictors can be one example. When the meshframe is coded as a whole, the frame can be regarded as an intra orinter coded mesh frame. In case of inter mesh frame, P or B type may befurther identified via signaling. Or, if a mesh frame is coded withfurther splitting inside a frame, assign prediction type for each of thesub-partitions occurs at S224. Each of the above-noted information maybe determined and signaled by a flag or the like, and like with S210 andS211 of FIG. 13 , said prediction features may occur at S226 and resultsof said prediction and signaling may occur at S227.

As such, although dynamic mesh sequence may require a large amount ofdata since it may consist of a significant amount of informationchanging over time, efficient compression technologies are required tostore and transmit such contents, and the above described features forFIGS. 20 and 21 represent such improved efficiencies by allowing atleast for improved mesh vertex 3D location prediction by either usingpreviously decoded vertices in the same mesh frame (intra prediction) orfrom a previous coded mesh frame (inter prediction).

Further, exemplary embodiments may generate the displacement vectors ofa third layer 2303 of a mesh, based on one or more the reconstructedvertices of its previous layer(s) such as a second layer 2302 and afirst layer 2301. Assuming the index of the second layer 2302 is T, thepredictors for vertices in third layer 2303 T+1 are generated based onthe reconstructed vertices of at least the current layer or second layer2302. An example of such layer based prediction structure is shownexample 1600 in FIG. 16 which illustrates reconstruction based vertexprediction: progressive vertex prediction using edge-basedinterpolation, where predictors are generated based on previouslydecoded vertices, not predictor vertices. The first layer 2301 may be amesh bounded by a first polygon 2340 having, as vertices thereof,decoded vertices, at boundaries thereof, and interpolated vertices,along ones of lines between ones of those decoded vertices. As theprogressive coding proceeds from the first layer 2301 to the secondlayer 2302, an additional polygon 2341 may be formed by displacementvectors from ones of the interpolated vertices of the first layer toadditional vertices of the second layer 2302, and as such, a totalnumber of vertices of the second layer 2302 may be greater than that ofthe first layer 2301. Likewise, proceeding to the third layer 2303, theadditional vertices of the second layer 2302, along with the decodedvertices from the first layer 2301, may then serve in the coding in asimilar manner as did the decoded vertices served in proceeding from thefirst layer 2301 to the second layer 2303; that is, multiple additionalpolygons may be formed. As note, see the example 1900 in FIG. 19illustrating such progressive coding where, unlike in FIG. 16 , theexample 1900 illustrates that, in proceeding from the first layer 2601to the second layer 2603 and then to the third layer 2603, each of theadditionally formed polygons may be entirely within a polygon formed bybounds of the first layer 2601.

For such example 1600, see the example flowchart 1500 of FIG. 15 wheresince the interpolated vertices on the current layer are predictedvalues, such values need to be reconstructed, before being used togenerate predictors of vertices on the next layer. This is done bycoding a base mesh at S231, implementing vertices prediction as such atS232, then at S233 adding the decoded displacement vectors of thecurrent layer to the vertex's predictors, such as of layer 2302. Thenthe reconstructed vertices of this layer 2303, together with all decodedvertices of previous layer(s), such as checking for addition verticesvalues of such layers at S234, can be used to generate and signal thepredictor vertices of next layer 2303 at S235. This process can also besummarized as follows: Let P[t](Vi) represent the predictor of vertex Vion a layer t; let R[t](Vi) represent the reconstructed vertex Vi onlayer t; let D[t](Vi) represent the displacement vector of vertex Vi onlayer t; let f(*) represent the predictor generator, which, inparticular, can be the average of the two existing vertices. Then foreach layer t, there is the following according to exemplary embodiments:

P[t](Vi)=f(R[s|s<t](Vj), R[m|m<t](Vk)), where

Vj and Vk are reconstructed vertices of previous layers

R[t](Vi)=P[t](Vi)+D[t](Vi)   Eq. (1)

Then, for all vertices in one mesh frame, divide them into layer 0 (thebase mesh), layer 1, layer 2, . . . Etc. Then the reconstruction ofvertices on one layer relies on the reconstruction of those on previouslayer(s). In the above, each of P, R and D represents a 3D vector underthe context of 3D mesh representation. D is the decoded displacementvector, and quantization may or may not apply to this vector.

According to exemplary embodiments, the vertex prediction usingreconstructed vertices may only apply to certain layers. For example,layer 0 and layer 1. For other layers, the vertex prediction can stilluse neighboring predictor vertices without adding displacement vectorsto them for reconstruction. So that these other layers can be processedat the same time without waiting one previous layer to reconstruct.According to exemplary embodiments, for each layer, whether to choosereconstruction based vertex prediction or predictor based vertexprediction, can be signaled, or the layer (and its subsequent layers)that does not use reconstruction based vertex prediction, can besignaled.

For the displacement vectors whose vertex predictors are generated byreconstructed vertices, quantization can be applied to them, withoutfurther performing transformation, such as wavelet transform, etc. Forthe displacement vectors whose vertex predictors are generated by otherpredictor vertices, transformation may be needed and quantization can beapplied to the transform coefficients of those displacement vectors.

As such, since a dynamic mesh sequence may require a large amount ofdata since it may consist of a significant amount of informationchanging over time. Therefore, efficient compression technologies arerequired to store and transmit such contents. In the framework ofinterpolation-based vertex prediction method described above, oneimportant procedure is to compress the displacement vectors, and thistakes up a major part in the coded bitstream, and the focus of thisdisclosure, and the features of FIG. 15 for example alleviate suchproblem by providing for such compression.

Further, similar to the other examples described above, even with thoseembodiments, a dynamic mesh sequence may nonetheless require a largeamount of data since it may consist of a significant amount ofinformation changing over time, and as such, efficient compressiontechnologies are required to store and transmit such contents. In theframework of 2D atlas sampling based methods indicated above, animportant advantage may be achieved by inferring the connectivityinformation from the sampled vertices plus boundary vertices on decoderside. This is a major part in decoding process, and a focus of furtherexamples described below.

According to exemplary embodiments, the connectivity information of thebase mesh can be inferred (derived) from the decoded boundary verticesand the sampled vertices for each chart on both encoder and decodersides.

As similarly described above, any triangulation method can be applied tocreate connectivity among vertices (including boundary vertices andsampled vertices). For charts without any sampling of internal vertices,such as with the internal vertices shown in example 1000 of FIG. 10 andexample 1800 of FIG. 18 described further below, similar methods ofcreating connectivity still apply although, according to exemplaryembodiments, it may be signaled to use different triangulation methodsfor boundary vertices and sampled vertices.

For example, according to exemplary embodiments, for every fourneighboring points in any sampled positions, it may be determinedwhether a number of occupied points is larger than or equal to 3(examples of occupied or unoccupied points are highlighted in FIG. 18which shows an occupancy map example 1800 which each circle representingan integer pixel), and the connectivity of triangles among the 4 pointscan be inferred by certain rules. For example, as illustrated in theexample 1700 of FIG. 17 , if 3 out of 4 points are determined to beoccupied, the shown examples (2), (3), (4), and (4), then those pointscan be interconnected directly to form a triangle as those examples; onthe other hand, if 4 points are all determined to be occupied, thenthose points are used to form two triangles as shown in example (1) ofFIG. 17 Note that different rules can be applied to different number ofneighboring points. This process may be implemented across many pointssuch as further illustrated in FIG. 18 . In this embodiment, thereconstructed mesh is a triangle mesh as in FIG. 17 and as in at leastas a regular triangle mesh in the internal portions of FIG. 18 , whichmay not be determined to not be signaled according to such regularitybut instead may be coded and decoded by inference rather than byindividual signaling, and as irregular triangles at the perimeter whichare to be signaled individually.

And in attempt to further reduce the complexity and data processing, aquad mesh of such regular internal triangles shown in FIG. 18 may beinferred as such quad mesh of the example (1) of FIG. 17 therebyreducing even the amount of complexity from inferring the internalregular triangles as instead inferring a reduced number of internalregular quad meshes.

According to exemplary embodiments, a quad mesh may be reconstructedwhen the 4 neighboring points are determined to be all occupied such asin the example (1) of FIG. 17 .

Extrapolating from the above-descriptions, as shown in FIG. 18 , it isillustrated that reconstructed mesh in the example 1800 can be a hybridtype, that is, some regions in the mesh frame generate triangle mesheswhile other regions generate quad meshes, and some of said trianglemeshes may be regular as compared to other triangle meshes therein andsome may be irregular, such as ones of the boundary though not necessaryall of such meshes on the boundary.

According to exemplary embodiments, such connectivity types can besignaled in high-level syntax, such as sequence header, slice header.

As mentioned above, connectivity information can be also reconstructedby explicitly signaling, such as for the irregularly shaped trianglemeshes. That is, if it is determined that a polygon cannot be recoveredby implicit rules, the encoder can signal the connectivity informationin the bitstream. And according to exemplary embodiments, the overheadof such explicit signaling may be reduced depending on the boundaries ofpolygons. For example, as shown with the example 1800 in FIG. 18 , theconnectivity information of triangles would be signaled to bereconstructed by both implicit rules, such as according to the regularexamples 2400 in FIG. 17 which may be inferred, and explicit signalingfor ones of the irregular shaped polygons shown at least on the meshboundaries in FIG. 18 .

According to embodiments, only the connectivity information betweenboundary vertices and sampled positions is determined to be signaled,while the connectivity information among the sampled positionsthemselves is inferred.

Also, in any of the embodiments, the connectivity information may besignaled by prediction, such that only the difference from the inferredconnectivity (as prediction) from one mesh to another may be signaled inbitstream.

As a note, the orientation of inferred triangles (such as to be inferredin a clockwise manner or in a counterclockwise manner per triangle) canbe either signaled for all charts in high-level syntax, such as sequenceheader, slice header, etc., or fixed (assumed) by encoder and decoderaccording to exemplary embodiments. The orientation of inferredtriangles can be also signaled differently for each chart.

As a further note, any reconstructed mesh may have differentconnectivity from the original mesh. For example, the original mesh maybe a triangle mesh, while the reconstructed mesh may be a polygonal mesh(e.g., quad mesh).

According to exemplary embodiments, the connectivity information of anybase vertices may not be signaled and instead the edges among basevertices may be derived using the same algorithm at both encoder anddecoder side. For example, see how the bottommost vertices in theexample 1800 are all occupied, and therefore, the coding may takeadvantage of such information by therefore determining that suchvertices are occupied as a base and thereby later inferring such thatthe connectivity information of any base vertices may not be signaledand instead the edges among base vertices may be derived using the samealgorithm at both encoder and decoder side. And according to exemplaryembodiments, interpolation of predicted vertices for the additional meshvertices may be based on the derived edges of the base mesh.

According to exemplary embodiments, a flag may be used to signal whetherthe connectivity information of the base vertices is to be signaled orderived, and such flag can be signaled at different level of thebitstream, such as at sequences level, frame level, etc.

According to exemplary embodiments, the edges among the base verticesare first derived using the same algorithm at both encoder and decoderside. Then compared with the original connectivity of the base meshvertices, the difference between the derived edges and the actual edgeswill be signaled. Therefore, after decoding the difference, the originalconnectivity of the base vertices can be restored.

In one example, for a derived edge, if determined to be wrong whencompared to the original edge, such information may signaled in thebitstream (by indicating the pair of vertices that form this edge); andfor an original edge, if not derived, may be signaled in the bitstream(by indicating the pair of vertices that form this edge). Further,connectivity on boundary edges and vertex interpolation involvingboundary edges may be done separately from the internal vertices andedges.

Accordingly, by exemplary embodiments described herein, the technicalproblems noted above may be advantageously improved upon by one or moreof these technical solutions. For example, since a dynamic mesh sequencemay require a large amount of data since it may consist of a significantamount of information changing over time, and therefore, the exemplaryembodiments described herein represent at least efficient compressiontechnologies to store and transmit such contents.

The above-described embodiments may be further applied to instance-basedmesh coding, where an instance may be a mesh of an object or a part ofan object. For example, the illustration example 2100 of FIG. 21illustrates a mesh example 2801 in which various instances 2802(representing a mesh of a cup), 2803 (representing a mesh of a spoon),and 2804 (representing a mesh of a plate) are present and may beseparated and coded respectively. And each of the instances 2801, 2802,2803, and 2804 are illustrated in respective ones of bounding boxeswhich will be described further below, but, as a note, it may beconsidered that the instance 2801 may be illustrated as a bounded by a“mesh-based bounding box” whereas each of instances 2802, 2803, and 2804may be considered illustrated as bounding by respective ones of an“instance-based bounding box.”

According to exemplary embodiments, the proposed methods may be usedseparately or combined in any order. The proposed methods may be usedfor arbitrary polygon mesh, but even though only a triangle mesh mayhave been used for demonstration of various embodiments. As noted above,it will be assumed that an input mesh may contain one or multipleinstances, that a submesh is a part of input mesh with an instance ormultiple instance, and that multiple instances can be grouped to form asubmesh.

In that light, FIG. 20 illustrates an example 2000 in which it isproposed to separately quantize different objects or parts at a giveninput bitdepth (where that bitdepth may be referred to as “QP”). Forexample, at 2701 an one or more input meshes may be obtained and eachseparated into multiple submeshes. A submesh can be an object, aninstance of an object or a segmented region, and will be quantized atS2702 independently according to exemplary embodiments.

According to exemplary embodiments, a mesh

with m points in (x, y, z) coordinate may be quantized at S2702 by a QPbitdepth. The quantization step size for all three dimensions (x, y, z)may be decided based on a largest length of the bounding box in alldimension—d_(bbox)>0. And same quantization step size may applied atS2704 for all objects, identified at S2703, in the mesh as

$\begin{matrix}{{\Delta_{qp} = \frac{d_{bbox}}{2^{QP} - 1}},} & {{Eq}.(1)}\end{matrix}$

and a scalar quantization thereof may applied for the j-th point at i-thcoordinate a_(ij) as

$\begin{matrix}{{{\overset{\sim}{a}}_{ij} = \left\lfloor {\frac{a_{ij} - \theta_{i}}{\Delta_{qp}} + \theta_{QP}} \right\rfloor},{i \in \left\{ {x,y,z} \right\}},{j \in \left\lbrack {1,\ldots,m} \right\rbrack},} & {{Eq}.(2)}\end{matrix}$

where θ_(QP)=0.5 is an offset parameter for quantization. θ_(i) is theminimum coordinate of the mesh in

at i-th dimension. Notation └⋅┘ stands for the floor rounding operator.And the dequantized coordinate may be calculated with uniformdequantization as follow

â _(ij) =ã _(ij)* Δ_(qp)+θ_(i) , i∈{x, y, z},j ∈[1, . . . , m]   Eq. (3)

with the mean square error of quantization as

$\begin{matrix}{\epsilon_{QP} = {\frac{1}{n}{\sum_{j}^{m}\left( {a_{ij} - {\hat{a}}_{ij}} \right)^{2}}}} & {{Eq}.(4)}\end{matrix}$

However, in complex scenes, a largest object is the background which mayrelatively often be simple and can tolerate a higher quantization stepsize. Meanwhile, the main objects are at smaller scale and suffer hugequantization error which may be accounted for by various embodimentsdescribed further below.

Therefore, as shown in the example 2200 in FIG. 22 , as the maximumlength of the bounding box of the input mesh d_(bbox) may always be setequal to or larger than the maximum length of the bounding box of eachinstance d_(bbox) ^(j) as

$\begin{matrix}{{d_{bbox} \geq {\max\limits_{j \in {\mathbb{O}}}\left\{ d_{bbox}^{j} \right\}}},} & {{Eq}.(5)}\end{matrix}$

where

is the set of all instances or segmentation in the input mesh.

At a given bitdepth QP, the quantization step size of every instance,each of instances 2802 (representing a mesh of a cup), 2803(representing a mesh of a spoon), and 2804 (representing a mesh of aplate), may always smaller than or equal to the mesh-based quantizationstep size that satisfies Δ_(qp) ^(j)≤Δqp, ∀j∈

.

Therefore, the quantization error for each instance becomes smaller,thus reducing the overall quantization error.

According to various embodiments, the bitdepth may be assignedadaptively for each instance/region, referred to as a “submesh” inS2902, and may be decided based on the face density of that particularinstance. Each submesh may be obtained from the volumetric data of themesh which may itself have signaled each instance within the meshindividually, and each submesh being derived from that mesh on perinstance basis at S2902. For example, each of the instances 2802, 2803,and 2804 may be assigned its own respective bitdepth, at S2904,depending on its own particular face density or numbers of vertices,forming one or more of the above-described polygons, therein. Ingeneral, the more faces each instance has, which may be determined atS2903 by counting a number of such polygons therein or the like, theless quantization should be applied at S2702 to that instance. Forexample, given a mesh

, a total number of faces is n, and corresponding faces for submesh k-this n_(k) that satisfies

n=Σ_(k=1) ^(K)n_(k), n_(k)>0   Eq. (6)

where K is the total number of submeshes. The submesh face density isdefined as

$\frac{n_{k}}{V_{bbox}^{k}}$

with

V_(bbox) ^(k) standing for the volume of the bounding box set at S2906of the k-th submesh. Then in one example, the adaptive quantization forinstance k, referred to as QP_(k) ^(b) can be defined in a limited range[QP_(min), QP_(max)] as

$\begin{matrix}{{QP}_{k} = {{{Clip}\left( {{{QP}*\frac{n_{k}*V_{bbox}}{n*V_{bbox}^{k}}},{QP}_{\min},{QP}_{\max}} \right)}.}} & {{Eq}.(7)}\end{matrix}$

According to various embodiments, a mesh is represented as a base-mesh Band its corresponding displacement D and quantized at S2702 at differentbitdepth. For example, for the k-th object, the bithdepth base meshQP_(k) ^(b) can be calculated from Eq. (3), and the bitdepth of itsdisplacement QP_(k) ^(d) could be derived as

QP _(k) ^(d)=└α_(k) ×QP _(k) ^(b)+β_(k)┘,   Eq. (8)

with α_(k), β_(k) is the adaptive scaling factor and offset for the jthobject. In one example, α_(k)=1 and β_(k)=2.

According to various embodiments, adaptive bitdepth parameters based onminimizing distortion may be used. For example, given an input bithdepthQP, the mean squared error (MSE) of a quantization method is ϵ_QP may beas in Eq. (4). The MSE of each submesh is derived as ϵ_QP{circumflexover ( )}k =ω_k*ϵ_QP,∀k∈[1, . . . ,K], where ω_k>0 is a weightingfactor. In one example, ω_k=1 ∀k. A linear search is performed for eachsubmesh to find the best bithdepth for base mesh that satisfies

$\begin{matrix}{{{QP}_{k}^{b} = {\min\limits_{q \in {\lbrack{{QP}_{\min},{QP}_{\max}}\rbrack}}{❘{\epsilon_{q} - {\omega_{k}\epsilon_{QP}}}❘}_{2}^{2}}},} & {{Eq}.(9)}\end{matrix}$

Additionally, a best bithdepth for displacement may also obtained via

$\begin{matrix}{{{QP}_{k}^{d} = {\min\limits_{{q \in {\lbrack{{QP}_{\min},{QP}_{\max}}\rbrack}},\alpha,\beta}{❘{\epsilon_{q} - {\omega_{k}\epsilon_{QP}}}❘}_{2}^{2}}},} & {{Eq}.(10)}\end{matrix}$

According to exemplary embodiments, there may be signaling ofquantization for each object such as by signaling at S2907 signalbithdepth through bitstream. The set of base quantization bitdepth inthe increasing order may be {QP_(k) ^(b)}_(k=0, . . . ,K) withcorresponding displacement quantization bitdepth {QP_(k)^(d)}_(k=0, . . . ,K). This information may be signaled as mesh instanceparameter syntax. For signaling, b₀ bits may be used to signal abounding box offset θ_(i). To avoid signaling overhead, all instancesmay share the same bounding box offset. Number K−1 is limited to b₁ bit,the maximum base quantization bithdepth is b₂ bit, the maximumdifference in bitdepth between base and displacement is b₃ bit. In oneexample, b₁=4, b₂=5, b₃=4. An example syntax table is shown below, wherethe instances are arranged in the order of ascending quantizationvalues. In this way, the signaled quantization difference for eachinstance may be always non-negative. In a more general case, theinstances may not be arranged by quantization values, for each instance,and in addition to the absolute difference, the sign may also besignaled.

mesh_instance_parameter_set( ) {  for (i = 0; i < num_dim; i++) {  mips_min_bbox [i] /* θ_(i) */ i(b₀)  }  mips_num_instances_minus1 /* K− 1 */ u(b₁)  mips_base_bithdepth_minus1 /* QP₀ ^(b) − 1 */ u(b₂) misp_dist_bitdepth[0] /*QP₀ ^(d) − QP₀ ^(b)*/  for (k = 1; j <=mips_num_instance_minus1;j++) {   mips_base_bitdepth [k-1] /* QP_(k)^(b) − QP_(k−1) ^(b) */ u(b₁)   mips_dist_bitdepth[k] /*QP_(k) ^(d) −QP_(k) ^(b)*/ i(b₃)  } }where

-   -   u(n) is unsigned integer using n bits, i(n) is integer using n        bits, and mips_quant( ) is a series of signaling data,    -   mips_min_bbox[k] is the minimum of the bounding box at i-th        dimension,    -   mips_num_instances_minus1 is the number of instances−1 in the        mesh,    -   mips_base_bitdepth_minus 1 is the bitdepth of the first instance        in the order,    -   mips_base_quant[k] is the difference in quantization of the        (k+1)-th and k-th submesh. As the quantization set is sorted in        the increasing order, this number is always non-negative, and    -   mips_dist_quant[k] is the k-th quantization data for base mesh        bithdepth.

According to various embodiments, multiple instances may be grouped to Kgroups with a same bitdepth to reduce the signaling overhead. Instancesmay be clustered based on the maximum distance of the bounding boxd_(bbox) ^(j) with a simple clustering method like K-mean clustering.

The techniques described above, can be implemented as computer softwareusing computer-readable instructions and physically stored in one ormore computer-readable media or by a specifically configured one or morehardware processors. For example, FIG. 23 shows a computer system 2300suitable for implementing certain embodiments of the disclosed subjectmatter.

The computer software can be coded using any suitable machine code orcomputer language, that may be subject to assembly, compilation,linking, or like mechanisms to create code comprising instructions thatcan be executed directly, or through interpretation, micro-codeexecution, and the like, by computer central processing units (CPUs),Graphics Processing Units (GPUs), and the like.

The instructions can be executed on various types of computers orcomponents thereof, including, for example, personal computers, tabletcomputers, servers, smartphones, gaming devices, internet of thingsdevices, and the like.

The components shown in FIG. 23 for computer system 2300 are exemplaryin nature and are not intended to suggest any limitation as to the scopeof use or functionality of the computer software implementingembodiments of the present disclosure. Neither should the configurationof components be interpreted as having any dependency or requirementrelating to any one or combination of components illustrated in theexemplary embodiment of a computer system 2300.

Computer system 2300 may include certain human interface input devices.Such a human interface input device may be responsive to input by one ormore human users through, for example, tactile input (such as:keystrokes, swipes, data glove movements), audio input (such as: voice,clapping), visual input (such as: gestures), olfactory input (notdepicted). The human interface devices can also be used to capturecertain media not necessarily directly related to conscious input by ahuman, such as audio (such as: speech, music, ambient sound), images(such as: scanned images, photographic images obtain from a still imagecamera), video (such as two-dimensional video, three-dimensional videoincluding stereoscopic video).

Input human interface devices may include one or more of (only one ofeach depicted): keyboard 2301, mouse 2302, trackpad 2303, touch screen2310, joystick 2305, microphone 2306, scanner 2308, camera 2307.

Computer system 2300 may also include certain human interface outputdevices. Such human interface output devices may be stimulating thesenses of one or more human users through, for example, tactile output,sound, light, and smell/taste. Such human interface output devices mayinclude tactile output devices (for example tactile feedback by thetouch-screen 2310, or joystick 2305, but there can also be tactilefeedback devices that do not serve as input devices), audio outputdevices (such as: speakers 2309, headphones (not depicted)), visualoutput devices (such as screens 2310 to include CRT screens, LCDscreens, plasma screens, OLED screens, each with or without touch-screeninput capability, each with or without tactile feedback capability—someof which may be capable to output two dimensional visual output or morethan three dimensional output through means such as stereographicoutput; virtual-reality glasses (not depicted), holographic displays andsmoke tanks (not depicted)), and printers (not depicted).

Computer system 2300 can also include human accessible storage devicesand their associated media such as optical media including CD/DVD ROM/RW2320 with CD/DVD 2311 or the like media, thumb-drive 2322, removablehard drive or solid state drive 2323, legacy magnetic media such as tapeand floppy disc (not depicted), specialized ROM/ASIC/PLD based devicessuch as security dongles (not depicted), and the like.

Those skilled in the art should also understand that term “computerreadable media” as used in connection with the presently disclosedsubject matter does not encompass transmission media, carrier waves, orother transitory signals.

Computer system 2300 can also include interface 2399 to one or morecommunication networks 2398. Networks 2398 can for example be wireless,wireline, optical. Networks 2398 can further be local, wide-area,metropolitan, vehicular and industrial, real-time, delay-tolerant, andso on. Examples of networks 2398 include local area networks such asEthernet, wireless LANs, cellular networks to include GSM, 3G, 4G, 5G,LTE and the like, TV wireline or wireless wide area digital networks toinclude cable TV, satellite TV, and terrestrial broadcast TV, vehicularand industrial to include CANBus, and so forth. Certain networks 2398commonly require external network interface adapters that attached tocertain general-purpose data ports or peripheral buses (2350 and 2351)(such as, for example USB ports of the computer system 2300; others arecommonly integrated into the core of the computer system 2300 byattachment to a system bus as described below (for example Ethernetinterface into a PC computer system or cellular network interface into asmartphone computer system). Using any of these networks 2398, computersystem 2300 can communicate with other entities. Such communication canbe uni-directional, receive only (for example, broadcast TV),uni-directional send-only (for example CANbusto certain CANbus devices),or bi-directional, for example to other computer systems using local orwide area digital networks. Certain protocols and protocol stacks can beused on each of those networks and network interfaces as describedabove.

Aforementioned human interface devices, human-accessible storagedevices, and network interfaces can be attached to a core 2340 of thecomputer system 2300.

The core 2340 can include one or more Central Processing Units (CPU)2341, Graphics Processing Units (GPU) 2342, a graphics adapter 2317,specialized programmable processing units in the form of FieldProgrammable Gate Areas (FPGA) 2343, hardware accelerators for certaintasks 2344, and so forth. These devices, along with Read-only memory(ROM) 2345, Random-access memory 2346, internal mass storage such asinternal non-user accessible hard drives, SSDs, and the like 2347, maybe connected through a system bus 2348. In some computer systems, thesystem bus 2348 can be accessible in the form of one or more physicalplugs to enable extensions by additional CPUs, GPU, and the like. Theperipheral devices can be attached either directly to the core's systembus 2348, or through a peripheral bus 2349. Architectures for aperipheral bus include PCI, USB, and the like.

CPUs 2341, GPUs 2342, FPGAs 2343, and accelerators 2344 can executecertain instructions that, in combination, can make up theaforementioned computer code. That computer code can be stored in ROM2345 or RAM 2346. Transitional data can be also be stored in RAM 2346,whereas permanent data can be stored for example, in the internal massstorage 2347. Fast storage and retrieval to any of the memory devicescan be enabled through the use of cache memory, that can be closelyassociated with one or more CPU 2341, GPU 2342, mass storage 2347, ROM2345, RAM 2346, and the like.

The computer readable media can have computer code thereon forperforming various computer-implemented operations. The media andcomputer code can be those specially designed and constructed for thepurposes of the present disclosure, or they can be of the kind wellknown and available to those having skill in the computer software arts.

As an example and not by way of limitation, the computer system havingarchitecture 2300, and specifically the core 2340 can providefunctionality as a result of processor(s) (including CPUs, GPUs, FPGA,accelerators, and the like) executing software embodied in one or moretangible, computer-readable media. Such computer-readable media can bemedia associated with user-accessible mass storage as introduced above,as well as certain storage of the core 2340 that are of non-transitorynature, such as core-internal mass storage 2347 or ROM 2345. Thesoftware implementing various embodiments of the present disclosure canbe stored in such devices and executed by core 2340. A computer-readablemedium can include one or more memory devices or chips, according toparticular needs. The software can cause the core 2340 and specificallythe processors therein (including CPU, GPU, FPGA, and the like) toexecute particular processes or particular parts of particular processesdescribed herein, including defining data structures stored in RAM 2346and modifying such data structures according to the processes defined bythe software. In addition or as an alternative, the computer system canprovide functionality as a result of logic hardwired or otherwiseembodied in a circuit (for example: accelerator 2344), which can operatein place of or together with software to execute particular processes orparticular parts of particular processes described herein. Reference tosoftware can encompass logic, and vice versa, where appropriate.Reference to a computer-readable media can encompass a circuit (such asan integrated circuit (IC)) storing software for execution, a circuitembodying logic for execution, or both, where appropriate. The presentdisclosure encompasses any suitable combination of hardware andsoftware.

While this disclosure has described several exemplary embodiments, thereare alterations, permutations, and various substitute equivalents, whichfall within the scope of the disclosure. It will thus be appreciatedthat those skilled in the art will be able to devise numerous systemsand methods which, although not explicitly shown or described herein,embody the principles of the disclosure and are thus within the spiritand scope thereof.

What is claimed is:
 1. A method for video coding, the method performedby at least one processor and comprising: obtaining an input meshcomprising volumetric data of at least one three-dimensional (3D) visualcontent; deriving a plurality of submeshes of the input mesh from aframe of the volumetric data, each of the submeshes comprising arespective one of instances of objects, and at least a first submesh anda second submesh from the plurality of the submeshes overlap each otherin the frame; setting a first bitdepth to the first submesh and a secondbitdepth to the second submesh, the first bitdepth being different thanthe second bitdepth; quantizing the first submesh and the second submeshbased on the first bitdepth and the second bitdepth respectively; andsignaling a result of quantizing the first submesh and the secondsubmesh.
 2. The method for video coding according to claim 1, whereinthe volumetric data comprises the first submesh and the second submeshoverlapped with each other and bounded by a bounding box, whereinderiving the plurality of submeshes comprises bounding each of theinstances of the object by respective ones of second bounding boxes, andwherein, at any of the first bitdepth and the second bitdepth, aquantization step size of any of the first submesh and the secondsubmesh is less than a quantization step size of the first submesh andthe second submesh overlapped with each other and bounded by thebounding box.
 3. The method for video coding according to claim 2,wherein setting the first bitdepth is based on determining a first facedensity of the first submesh, and wherein setting the second bitdepth isbased on determining a second face density of the second submesh.
 4. Themethod for video coding according to claim 3, wherein quantizing thefirst submesh and the second submesh comprises: applying, based on thefirst bitdepth, a first level of quantization to the first submesh, andapplying, based on the second bitdepth, a second level of quantizationto the second submesh, and wherein the first level is set to be lessthan the second level based on determining that the first bitdepthindicates that the first submesh has a greater one of the face densitiesthan indicated by the second bitdepth set to the second submesh.
 5. Themethod for video coding according to claim 3, wherein the first submeshis bounded by a first one of the second bounding boxes, wherein thesecond submesh is bounded by a second one of the second bounding boxes,and wherein determining the first face density and the second facedensity comprises comparing numbers of faces of the first submesh andthe second submesh to respective ones of volumes of the first one of thesecond bounding boxes and the second one of the second bounding boxes.6. The method for video coding according to claim 2, wherein signalingthe result of quantizing the first submesh and the second submeshcomprises signaling that each of the first submesh and the secondsubmesh shares a same bounding box offset.
 7. The method for videocoding according to claim 1, wherein signaling the result of quantizingthe first submesh and the second submesh comprises signaling a totalnumber of the instances of the objects in the frame.
 8. The method forvideo coding according to 1, wherein signaling the result of quantizingthe first submesh and the second submesh comprises signaling adifference between quantization applied to the first submesh and thesecond submesh and sorting the difference as compared to otherquantization applied to other submeshes of the frame.
 9. The method forvideo coding according to claim 8, wherein the first bitdepth is appliedto at least one other of the other submeshes, and wherein signaling theresult of quantizing the first submesh and the second submesh comprisesgrouping the first submesh with the at least one other of the othersubmeshes based on determining that the first bitdepth is applied toboth the first submesh and the at least one other of the othersubmeshes.
 10. The method for video coding according to claim 1, whereinsetting the first bitdepth and the second bitdepth comprises derivingmean square errors of each of the first submesh and the second submeshat each of the first bitdepth and the second bitdepth.
 11. An apparatusfor video coding, the apparatus comprising: at least one memoryconfigured to store computer program code; at least one processorconfigured to access the computer program code and operate as instructedby the computer program code, the computer program code including:obtaining code configured to cause the at least one processor to obtainan input mesh comprising volumetric data of at least onethree-dimensional (3D) visual content; deriving code configured to causethe at least one processor to derive a plurality of submeshes of theinput mesh from a frame of the volumetric data, each of the submeshescomprising a respective one of instances of objects, and a first submeshand a second submesh from the plurality of submeshes overlap each otherin the frame; setting code configured to cause the at least oneprocessor to set a first bitdepth to the first submesh and a secondbitdepth to the second submesh, the first bitdepth being different thanthe second bitdepth; quantizing code configured to cause the at leastone processor to quantize the first submesh and the second submesh basedon the first bitdepth and the second bitdepth respectively; andsignaling code configured to cause the at least one processor to signala result of quantizing the first submesh and the second submesh.
 12. Theapparatus for video coding according to claim 11, wherein the volumetricdata comprises the first submesh and the second submesh overlapped witheach other and bounded by a bounding box, wherein deriving the pluralityof submeshes comprises bounding each of the instances of the object byrespective ones of second bounding boxes, and wherein, at any of thefirst bitdepth and the second bitdepth, a quantization step size of anyof the first submesh and the second submesh is less than a quantizationstep size of the first submesh and the second submesh overlapped witheach other and bounded by the bounding box.
 13. The apparatus for videocoding according to claim 12, wherein setting the first bitdepth isbased on determining a first face density of the first submesh, andwherein setting the second bitdepth is based on determining a secondface density of the second submesh.
 14. The apparatus for video codingaccording to claim 13, wherein quantizing the at least two of thesubmeshes comprises: applying, based on the first bitdepth, a firstlevel of quantization to the first submesh, and applying, based on thesecond bitdepth, a second level of quantization to the second submesh,and wherein the first level is set to be less than the second levelbased on determining that the first bitdepth indicates that the firstsubmesh has a greater one of the face densities than indicated by thesecond bitdepth set to the second submesh.
 15. The apparatus for videocoding according to claim 13, wherein the first submesh is bounded by afirst one of the second bounding boxes, wherein the second submesh isbounded by a second one of the second bounding boxes, and whereindetermining the first face density and the second face density comprisescomparing numbers of faces of the first submesh and the second submeshto respective ones of volumes of the first one of the second boundingboxes and the second one of the second bounding boxes.
 16. The apparatusfor video coding according to claim 12, wherein signaling the result ofquantizing the first submesh and the second submesh comprises signalingthat each of the first submesh and the second submesh shares a samebounding box offset.
 17. The apparatus for video coding according toclaim 11, wherein signaling the result of quantizing the first submeshand the second submesh comprises signaling a total number of theinstances of the objects in the frame.
 18. The apparatus for videocoding according to 11, wherein signaling the result of quantizing thefirst submesh and the second submesh comprises signaling a differencebetween quantization applied to the first submesh and the second submeshand sorting the difference as compared to other quantization applied toother submeshes of the frame.
 19. The apparatus for video codingaccording to claim 18, wherein the first bitdepth is applied to at leastone other of the other submeshes, and wherein signaling the result ofquantizing the first submesh and the second submesh comprises groupingthe first one of the first submesh and the second submesh with the atleast one other of the other submeshes based on determining that thefirst bitdepth is applied to both the first submesh and the at least oneother of the other submeshes.
 20. A non-transitory computer readablemedium storing a program causing a computer to: obtain an input meshcomprising volumetric data of at least one three-dimensional (3D) visualcontent; derive a plurality of submeshes of the input mesh from a frameof the volumetric data, each of the submeshes comprising a respectiveone of instances of objects, and at least a first submesh and a secondsubmesh from the plurality of submeshes overlap each other in the frame;set a first bitdepth to the first submesh and a second bitdepth to thesecond submesh, the first bitdepth being different than the secondbitdepth; quantize the first submesh and the second submesh based on thefirst bitdepth and the second bitdepth respectively; and signal a resultof quantizing the first submesh and the second submesh.